PyPi: Tensorflow

CVE-2021-37657

Safety vulnerability ID: 41132

This vulnerability was reviewed by experts

The information on this page was manually curated by our Cybersecurity Intelligence Team.

Created at Aug 12, 2021 Updated at Oct 25, 2024
Scan your Python projects for vulnerabilities →

Advisory

TensorFlow 2.3.4, 2.4.3, 2.5.1 and 2.6.0 include a fix for CVE-2021-37657: In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type 'tf.raw_ops.MatrixDiagV*'. The implementation (https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of 'k' is a valid tensor. The Tensorflow team has checked that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. The Tensorflow team has patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09.

Affected package

tensorflow

Latest version: 2.18.0

TensorFlow is an open source machine learning framework for everyone.

Affected versions

Fixed versions

Vulnerability changelog

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. See CVE-2021-37657.


CONFIRM:https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m
MISC:https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09: https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09

Resources

Use this package?

Scan your Python project for dependency vulnerabilities in two minutes

Scan your application

Severity Details

CVSS Base Score

HIGH 7.8

CVSS v3 Details

HIGH 7.8
Attack Vector (AV)
LOCAL
Attack Complexity (AC)
LOW
Privileges Required (PR)
LOW
User Interaction (UI)
NONE
Scope (S)
UNCHANGED
Confidentiality Impact (C)
HIGH
Integrity Impact (I)
HIGH
Availability Availability (A)
HIGH

CVSS v2 Details

MEDIUM 4.6
Access Vector (AV)
LOCAL
Access Complexity (AC)
LOW
Authentication (Au)
NONE
Confidentiality Impact (C)
PARTIAL
Integrity Impact (I)
PARTIAL
Availability Impact (A)
PARTIAL